This file is my general teaching statement, written at a fairly high level of abstraction; this is part of my job market file. The post directly below this one contains a more detailed description of my teaching portfolio.

Teaching statement

I am strongly committed to the craft of teaching, and I am particularly interested in, and proficient at, teaching courses that students often dread: statistics and computing for social science, and research methods more generally. I have served as our department’s lecturer for its large introductory statistics course on five occasions; I have also served as the lecturer of the department’s undergraduate research methods course twice and once as lecturer of its course in data management (along with other experience detailed below).

I am proud to report that I often succeed in engaging even students who expect to find the material dull; as one student wrote of my introductory statistics lecture, “Although I was not interested in the information, the professor made the class very interesting”. Even if a student feels that she or he is simply trying to “get through the course”, I take pride in helping them do so while giving them the chance to learn and develop their own skills. A characteristic comment is one delivered by a student in my advanced statistics laboratory: “I felt like I would not have been able to get through this class if it wasn’t for Griffin.”

This qualitative evidence can be corroborated by quantitative evidence from my course evaluations: as a lecturer, I achieved a weighted mean across methods and statistic courses of $4.48$ out of $5$ ($n = 147$). I have also won, or been nominated by the Sociology Department for, a number of teaching awards. In 2020, I was the winner of an Excellence in Teaching by a Teaching Assistant award from the department. I was also the department’s Nominee for the 2023–2024 Letters and Science Teaching Mentors Program as well as the department’s Nominee for the Campus Exceptional Service Award in 2021.

My broadest aim when teaching is to leave students with a healthy, rigorous skepticism of big claims: most of my students do not go on to conduct scientific research or need to recall formulae on a daily basis, but as citizens, they do frequently need to evaluate arguments made in the public sphere. I believe that learning to reason like a good social scientist serves as an object lesson in critical thinking more generally — students may not remember the nuts and bolts years later, but the experience of successfully mastering those details once leaves an appreciation for the art of reasoning that is hard to replicate by other means.

At a more concrete level, I have three fundamental goals for my teaching.

First, I hope for students to come away with mastery of the material — I want them to understand, rather than believe, what social scientists think. I strive to present students with ideas in their “zone of proximal development”: rather than inundate students with long lists of theoreticians or statisticians and expect them to struggle to memorize reductive renditions of “who said what”, I outline the basic concepts in sociological research methods and expect students to grapple with the arguments. For example, in my statistics lectures, I present brief demonstrations of properties of the variance that are new to most students but do not go beyond the level of algebra. While it is possible, and common, to simply tell students these properties, I generally do not ask students to memorize content on my say-so; if there is a complex or novel idea that I believe that they can understand, I ask them to understand it, and if an idea is truly too advanced for a given course, I avoid wading in those waters. In short, I want students to have a clear narrative arc for a course where they feel ownership of the ideas, and my highest aim is for them to actually enjoy what can be difficult material. I seek each semester to have every member of the course feel the way one of my introductory statistics students did: “[This] is single-handedly the best math class I’ve ever taken […] I was already nervous taking a course like this because I was never good at math. Yet, the professor has changed my whole outlook on math.”

Second, I strongly believe in student-oriented, hands-on learning. Even in lecture courses with more than $100$ students, I commit to memorizing the majority of my students’ names; I offer generous office hours, encourage students to attend, and generally find that many do. In the lecture hall, I use this rapport with students to teach in a “call and response” fashion, eliciting answers from students with relative ease, even when they are not entirely confident in their understanding yet. I insist that students develop their comprehension in a multifaceted, practical manner. I expect students to become comfortable with some pen-and-paper calculations and to be confident using statistical software. Even in the age of large language models, I hold that it is important for students to actually play with formulae, to be able to make mistakes and achieve the satisfaction of struggling and getting a correct answer, rather than to merely loosely understand the “gist.” I have found that many students in fact thrive when they see that, for example, they can calculate the correlation coefficient by hand for a small set of data and observe that it obeys all of the expected properties — the sign goes the direction they would hope and the strength is about what they would guess.

Finally, I seek to make the material relevant to students. When I teach statistics, the course culminates in a research project of their choosing. Students use real world data (typically the General Social Survey or Current Population Survey) and work with Stata or Python to answer questions that they are actually interested in. I provide detailed feedback on project proposals and the final products, even in large classes (with the help of teaching assistants, of course). I encourage students to explore controversial questions and to put their own views to the test. Students report to me sometimes that they update their priors based on the results, which I think is a strong measure of success: I know that I have given students the tools to answer questions with so much confidence that they are willing to change their minds.

It is worth mentioning that I put a great deal of effort into developing original, accessible materials when I teach, materials that correspond to the combination of intelligibility and rigor which I bring to the classroom. I have produced a full set of lecture notes for our introductory statistics course (SOC360), allowing me to do without a textbook, available here, along with a corresponding set of taped lectures and a video series introducing Stata. I also wrote a portion of my own introductory quantitative methods textbook for the general methods course (SOC357) here. My lab notes for a graduate course in statistics received extremely positive feedback; one student wrote in an evaluation that they felt “[s]o lucky I got to learn from him before he graduates.” A comprehensive description of my teaching portfolio, including lecture slides and code, is available here on my website.

Coming to my concrete teaching record, I have served as lecturer for “Statistics for Sociologists I” on five occasions and the TA once. I have also lectured “Social Research Methods” (SOC357) twice and “Data Management for Social Science” (SOC365) once.

Earlier in my career, I served as a TA, focusing on substantial courses related to my research focus. As a TA, I taught two sections of “Statistics for Sociologists II” (SOC361) for one semester, three to five sections of “American Society: How It Really Works” (SOC125) for four semesters, and five sections of “Population Problems” (SOC170) for two semesters.

In closing, I will mention the courses I am prepared to teach. First, I would be excited to teach any level of a statistics course aimed at the social sciences, including graduate courses, and any level of a research methods course. I am also happy to teach substantive courses on inequality, economic sociology, class and stratification, introductory demography, and American society writ large. I am finally very interested in developing new courses: I would be particularly interested in designing a course introducing advanced students to the literature on debates concerning inequality.